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<p>各种方便的Embedding加载（包括ELMo和BERT）、中间数据cache等，部分数据集与预训练模型的自动下载
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<p>提供多种神经网络组件以及复现模型（涵盖中文分词、命名实体识别、句法分析、文本分类、文本匹配、指代消解、摘要等任务）
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<p>Trainer提供多种内置Callback函数，方便实验记录、异常捕获等。
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                        <span class="top-title pre-line">相关项目</span>
                        <h2 id="fastnlp相关项目">FastNLP相关项目</h2>
<p>我们希望通过FastNLP可以帮助到NLP研究者进行更快更方便的研究。
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                            <span class="pre-line text-primary"> FastNLP </span>
                            fastNLP 是一款轻量级的自然语言处理（NLP）工具包。你既可以用它来快速地完成一个NLP任务， 也可以用它在研究中快速构建更复杂的模型。
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                            <span class="pre-line text-primary"> fitlog </span>
                            fitlog是一款集成了自动版本管理和自动日志记录两种功能的 Python 包，由复旦大学计算机科学技术学院 自然语言处理与深度学习组 的 fastNLP 团队开发的。它可以帮助你在进行实验时方便地保存当前的代码、参数和结果。
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                            <span class="pre-line text-primary"> FastRE </span>
                            随着知识图谱的使用越来越广泛，关系抽取作为知识图谱构建的基础，是当今最火热的研究方向之一。fastRE作为fastNLP的子项目，利用fastnlp提供的灵活而强大的基础功能，快捷便利的复现了各种经典关系抽取模型。方便大家在知识图谱项目中，开箱即用。
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                            <span class="pre-line text-primary"> FastHan </span>
                            fastHan是基于fastNLP与pytorch实现的中文自然语言处理工具，像spacy一样调用方便。 其内核为基于BERT的联合模型，其在13个语料库中进行训练，可处理中文分词、词性标注、依存分析、命名实体识别四项任务。fastHan共有base与large两个版本，分别利用BERT的前四层与前八层。base版本在总参数量150MB的情况下各项任务均有不错表现，large版本则接近甚至超越SOTA模型。
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                            <span class="pre-line text-primary"> FastSum </span>
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                            <span class="pre-line text-primary"> FastMatching </span>
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